Modelling human behaviour and event detection from videos

Automatic analysis of human behaviour in large collections of videos is gaining interest, even more so with the advent of file sharing sites such as YouTube. However, challenges still exist owing to several factors such as inter- and intra-class variations, cluttered backgrounds, occlusion, camera motion, scale, view and illumination changes. This research focuses on modelling human behaviour for action recognition in videos. The developed techniques are validated on large scale benchmark datasets and applied on real-world scenarios such as soccer videos. Three major contributions are made. The first contribution is in the area of proper choice of a feature representation for videos. This involved a study of state-of-the-art techniques for action recognition, feature extraction processing and dimensional reduction techniques so as to yield the best performance with optimal computational requirements. Secondly, temporal modelling of human behaviour is performed. This involved frequency analysis and temporal integration of local information in the video frames to yield a temporal feature vector. Current practices mostly average the frame information over an entire video and neglect the temporal order. Lastly, the proposed framework is applied and further adapted to real-world scenario such as soccer videos. A dataset consisting of video sequences depicting events of players falling is created from actual match data to this end and used to experimentally evaluate the proposed framework.

Molecular and serological detection of occult hepatitis B virus among healthy hepatitis B surface antigen-negative blood donors in Malaysia.

Background: Occult hepatitis B infections are becoming a major global threat, but the available data on its prevalence in various parts of the world are often divergent. Objective: This study aimed to detect occult hepatitis B virus in hepatitis B surface antigen-negative serum using anti-HBc as a marker of previous infection. Patient and Methods: A total of 1000 randomly selected hepatitis B surface antigen-negative sera from blood donors were tested for hepatitis B core antibody and hepatitis B surface antibody using an ELISA and nested polymerase chain reaction was done using primers specific to the surface gene (S-gene). Results: Of the 1000 samples 55 (5.5%) were found to be reactive, of which 87.3% (48/55) were positive for hepatitis B surface antibody, indicating immunity as a result of previous infection however, that does not exclude active infection with escaped mutant HBV. Nested PCR results showed the presence of hepatitis B viral DNA in all the 55 samples that were positive for core protein, which is in agreement with the hepatitis B surface antibody result. Conclusion: This study reveals the 5.5% prevalence of occult hepatitis B among Malaysian blood donors as well as the reliability of using hepatitis B core antibody in screening for occult hepatitis B infection in low endemic, low socioeconomic settings.

The Prevalence of Depression among patients and its detection by Primary Health Care Workers at Matawale Health Centre (Zomba)

Background Little information is available on the prevalence of depression in Malawi in primary health care settings and yet there is increased number of cases of depression presenting at tertiary level in severe form. Aim The aim of the study was to determine the prevalence of depression among patients and its detection by health care workers at a primary health care clinic in Zomba. Methods A cross-sectional survey was done among patients attending outpatient department at Matawale Health Centre, in Zomba from 1st July 2009 through to 31st July 2009. A total of 350 adults were randomly selected using systematic sampling. The “Self Reporting Questionnaire”, a questionnaire measuring social demographic factors and the Structured Clinical Interview for DSM-IV Axis I disorders Non-Patient Version (SCID-NP) were administered verbally to the participants. Findings The prevalence of depression among the patients attending the outpatients department was found to be 30.3% while detection rate of depression by clinician was 0%. Conclusion The results revealed the magnitude of depression which is prevalent in the primary health care clinic that goes undiagnosed and unmanaged. It is therefore recommended that primary health care providers do thorough assessments to address common mental disorders especially depression and they should be educated to recognise and manage depression appropriately at primary care level.

Behavioral and molecular genetics of reading-related AM and FM detection thresholds

Auditory detection thresholds for certain frequencies of both amplitude modulated (AM) and frequency modulated (FM) dynamic auditory stimuli are associated with reading in typically developing and dyslexic readers. We present the first behavioral and molecular genetic characterization of these two auditory traits. Two extant extended family datasets were given reading tasks and psychoacoustic tasks to determine FM 2 Hz and AM 20 Hz sensitivity thresholds. Univariate heritabilities were significant for both AM (h2 = 0.20) and FM (h2 = 0.29). Bayesian posterior probability of linkage (PPL) analysis found loci for AM (12q, PPL = 81 %) and FM (10p, PPL = 32 %; 20q, PPL = 65 %). Bivariate heritability analyses revealed that FM is genetically correlated with reading, while AM was not. Bivariate PPL analysis indicates that FM loci (10p, 20q) are not also associated with reading.

Student projects: plagiarism and assessment

Within the Information Technology degree programme of the University of Reading, the students undertake a major project in their final year. The module is both a hurdle to an honours degree and significant in terms of assessment weighting. The two year history so far has shown that bad citation and plagiarism are issues, and in one case called for the due referral of a project report. In the light of experience to date, we are focusing firstly on plagiarism prevention, giving generic advice on report writing and citation practice, and secondly on detection. In the longer term, I believe we need to reflect on what capabilities we should be creating in our undergraduates and therefore what and how we should be assessing them.

“I didn’t mean to steal someone else’s words!”:a forensic linguistic approach to detecting intentional plagiarism

The concept of plagiarism is not uncommonly associated with the concept of intellectual property, both for historical and legal reasons: the approach to the ownership of ‘moral’, nonmaterial goods has evolved to the right to individual property, and consequently a need was raised to establish a legal framework to cope with the infringement of those rights. The solution to plagiarism therefore falls most often under two categories: ethical and legal. On the ethical side, education and intercultural studies have addressed plagiarism critically, not only as a means to improve academic ethics policies (PlagiarismAdvice.org, 2008), but mainly to demonstrate that if anything the concept of plagiarism is far from being universal (Howard & Robillard, 2008). Even if differently, Howard (1995) and Scollon (1994, 1995) argued, and Angèlil-Carter (2000) and Pecorari (2008) later emphasised that the concept of plagiarism cannot be studied on the grounds that one definition is clearly understandable by everyone. Scollon (1994, 1995), for example, claimed that authorship attribution is particularly a problem in non-native writing in English, and so did Pecorari (2008) in her comprehensive analysis of academic plagiarism. If among higher education students plagiarism is often a problem of literacy, with prior, conflicting social discourses that may interfere with academic discourse, as Angèlil-Carter (2000) demonstrates, we then have to aver that a distinction should be made between intentional and inadvertent plagiarism: plagiarism should be prosecuted when intentional, but if it is part of the learning process and results from the plagiarist’s unfamiliarity with the text or topic it should be considered ‘positive plagiarism’ (Howard, 1995: 796) and hence not an offense. Determining the intention behind the instances of plagiarism therefore determines the nature of the disciplinary action adopted. Unfortunately, in order to demonstrate the intention to deceive and charge students with accusations of plagiarism, teachers necessarily have to position themselves as ‘plagiarism police’, although it has been argued otherwise (Robillard, 2008). Practice demonstrates that in their daily activities teachers will find themselves being required a command of investigative skills and tools that they most often lack. We thus claim that the ‘intention to deceive’ cannot inevitably be dissociated from plagiarism as a legal issue, even if Garner (2009) asserts that generally plagiarism is immoral but not illegal, and Goldstein (2003) makes the same severance. However, these claims, and the claim that only cases of copyright infringement tend to go to court, have recently been challenged, mainly by forensic linguists, who have been actively involved in cases of plagiarism. Turell (2008), for instance, demonstrated that plagiarism is often connoted with an illegal appropriation of ideas. Previously, she (Turell, 2004) had demonstrated by comparison of four translations of Shakespeare’s Julius Caesar to Spanish that the use of linguistic evidence is able to demonstrate instances of plagiarism. This challenge is also reinforced by practice in international organisations, such as the IEEE, to whom plagiarism potentially has ‘severe ethical and legal consequences’ (IEEE, 2006: 57). What plagiarism definitions used by publishers and organisations have in common – and which the academia usually lacks – is their focus on the legal nature. We speculate that this is due to the relation they intentionally establish with copyright laws, whereas in education the focus tends to shift from the legal to the ethical aspects. However, the number of plagiarism cases taken to court is very small, and jurisprudence is still being developed on the topic. In countries within the Civil Law tradition, Turell (2008) claims, (forensic) linguists are seldom called upon as expert witnesses in cases of plagiarism, either because plagiarists are rarely taken to court or because there is little tradition of accepting linguistic evidence. In spite of the investigative and evidential potential of forensic linguistics to demonstrate the plagiarist’s intention or otherwise, this potential is restricted by the ability to identify a text as being suspect of plagiarism. In an era with such a massive textual production, ‘policing’ plagiarism thus becomes an extraordinarily difficult task without the assistance of plagiarism detection systems. Although plagiarism detection has attracted the attention of computer engineers and software developers for years, a lot of research is still needed. Given the investigative nature of academic plagiarism, plagiarism detection has of necessity to consider not only concepts of education and computational linguistics, but also forensic linguistics. Especially, if intended to counter claims of being a ‘simplistic response’ (Robillard & Howard, 2008). In this paper, we use a corpus of essays written by university students who were accused of plagiarism, to demonstrate that a forensic linguistic analysis of improper paraphrasing in suspect texts has the potential to identify and provide evidence of intention. A linguistic analysis of the corpus texts shows that the plagiarist acts on the paradigmatic axis to replace relevant lexical items with a related word from the same semantic field, i.e. a synonym, a subordinate, a superordinate, etc. In other words, relevant lexical items were replaced with related, but not identical, ones. Additionally, the analysis demonstrates that the word order is often changed intentionally to disguise the borrowing. On the other hand, the linguistic analysis of linking and explanatory verbs (i.e. referencing verbs) and prepositions shows that these have the potential to discriminate instances of ‘patchwriting’ and instances of plagiarism. This research demonstrates that the referencing verbs are borrowed from the original in an attempt to construct the new text cohesively when the plagiarism is inadvertent, and that the plagiarist has made an effort to prevent the reader from identifying the text as plagiarism, when it is intentional. In some of these cases, the referencing elements prove being able to identify direct quotations and thus ‘betray’ and denounce plagiarism. Finally, we demonstrate that a forensic linguistic analysis of these verbs is critical to allow detection software to identify them as proper paraphrasing and not – mistakenly and simplistically – as plagiarism.

The effectiveness of direct -instruction and student -centered teaching methods on students' functional understanding of plagiarism

In an attempt to improve students' functional understanding of plagiarism a variety of approaches were tried within the context of a more comprehensive information literacy program. Sessions were taught as a one hour "module" inside a required communications skills class at a small private university. Approaches taken included control sessions (a straightforward PowerPoint presentation of the material), direct instruction sessions (featuring mostly direct lecture but with some seatwork as well), and student-centered sessions (utilizing role playing and group exercises). Students were taught basic content and definitions regarding plagiarism, what circumstances or instances constitute plagiarism, where to go for help in avoiding plagiarism, and what constitutes appropriate paraphrasing and citation. Pre-test and post-test scores determined students' functional understanding primarily by their ability to recognize properly and improperly paraphrased text, content understanding by their combined total score on a multiple choice quiz, and their attitude and conceptual understanding by their ability to recognize circumstances which would constitute plagiarism. While students improved across all methods the study was unable to identify one that performed significantly better than the others. The results supported the need for more education with regard to plagiarism and suggested a need for perhaps more time on task and/or a mixed approach towards conveying the content.

Analysis and detection of cognitive load and frustration in drivers' speech

Non-driving related cognitive load and variations of emotional state may impact a driver’s capability to control a vehicle and introduces driving errors. Availability of reliable cognitive load and emotion detection in drivers would benefit the design of active safety systems and other intelligent in-vehicle interfaces. In this study, speech produced by 68 subjects while driving in urban areas is analyzed. A particular focus is on speech production differences in two secondary cognitive tasks, interactions with a co-driver and calls to automated spoken dialog systems (SDS), and two emotional states during the SDS interactions - neutral/negative. A number of speech parameters are found to vary across the cognitive/emotion classes. Suitability of selected cepstral- and production-based features for automatic cognitive task/emotion classification is investigated. A fusion of GMM/SVM classifiers yields an accuracy of 94.3% in cognitive task and 81.3% in emotion classification.

A spoofing detection method for civilian L1 GPS and the E1-B Galileo Safety of Life service

This paper describes an effective method for signal-authentication and spoofing detection for civilian GNSS receivers using the GPS L1 C/A and the Galileo E1-B Safety of Life service. The paper discusses various spoofing attack profiles and how the proposed method is able to detect these attacks. This method is relatively low-cost and can be suitable for numerous mass-market applications. This paper is the subject of a pending patent.

Advances in skin cancer early detection and diagnosis

OBJECTIVES: To provide an overview of 1) traditional methods of skin cancer early detection, 2) current technologies for skin cancer detection, and 3) evolving practice models of early detection. DATA SOURCES: Peer-reviewed databased articles and reviews, scholarly texts, and Web-based resources. CONCLUSION: Early detection of skin cancer through established methods or newer technologies is critical for reducing both skin cancer mortality and the overall skin cancer burden. IMPLICATIONS FOR NURSING PRACTICE: A basic knowledge of recommended skin examination guidelines and risk factors for skin cancer, traditional methods to further examine lesions that are suspicious for skin cancer and evolving detection technologies can guide patient education and skin inspection decisions.

Protocol : A highly sensitive RT-PCR method for detection and quantification of microRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.

Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.